Triple

T31642844
Position Surface form Disambiguated ID Type / Status
Subject Uvas Creek E807501 entity
Predicate hasDam P8736 FINISHED
Object Uvas Dam
Uvas Dam is an earthen reservoir dam in Santa Clara County, California, that impounds Uvas Creek to provide water storage and flood control.
E1970852 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Uvas Dam | Statement: [Uvas Creek, hasDam, Uvas Dam]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Uvas Dam
Triple: [Uvas Creek, hasDam, Uvas Dam]
Generated description
Uvas Dam is an earthen reservoir dam in Santa Clara County, California, that impounds Uvas Creek to provide water storage and flood control.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f348d9ce58819093ea2da83cbeeec1 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a91c1d3c8190b7c11e5a75921aff completed May 3, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b79df559c819098e635fcb632e607 completed June 12, 2026, 3:15 a.m.
NEDg Description generation batch_6a2b7a9bed2881908e5ca2d02afeaeff completed June 12, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a2b7b3574f881908e98863d147351de completed June 12, 2026, 3:21 a.m.
Created at: April 30, 2026, 10:50 p.m.